typ1K4L™ — CS2 Stats

76561198863252930[U:1:902987202]

2,646Tracked matches52%Win rate2020Tracked since

2,188Hours in CS

CSDB Rating5.9 SolidAggressive Rifler

Premier CS Rating14,708Blue band · top ~29.9% of ranked players (population est.)

CSDB Leaderboard#7015 of 10590 tracked

FaceitLevel 4Top 81.0% of ranked FACEIT players

WingmanMaster Guardian I

Ladder ranks via Leetify

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Performance scores

Aim77

Positioning50

Utility63

0–100 skill scores via Leetify.

Recent form

HOT48–46–6Last 10048%Win rateWWWWWWLLWW

Last 10 vs previous 10: +40pp win rate · -0.01 avg rating

Player DNA

Primary style: Aggressive Rifler — Takes opening fights often, backed by a strong aim profile.

Aim7.7

Aggression7.7

Utility6.3

Positioning5.0

Opening Duels3.4

Clutch2.0

Strong CT-side openerEffective flashes

Style profile from tracked-match aggregates — how this player plays, not how good they are. Classification rules are deterministic and documented in code.

Your pro match

Plays most like b1t 92% playstyle similarity

Most alike: utility contribution, opening-duel success.

Where you differ: lower positioning profile; lower aim profile.

Similarity of playstyle shape across shared dimensions — it says how you play, not that you play at their level. Full comparison →

Strengths & areas to improve

Areas to improve

T-side openings. Opening success drops from 51% on CT to 36% on T — the same duels are being taken with worse setups on the attacking side.

Reaction time. 563ms from enemy-visible to first shot leaves fights decided before they start — warmup routines move this number more than anything else.

Generated by fixed rules over this profile's own numbers — no model, no guessing; silent when the sample is too small to support a claim.

CSDB Rating breakdown

Aim7.7

Positioning5.0

Utility6.3

Mechanics7.2

Opening Duels3.4

Win Impact5.6

Composite 5.9/10 (Solid), a weighted mean of the bars with a small opposition adjustment (×0.95 for this rank band). Formula versioned (v1) and documented in code.

Trends

Match rating-0.02−0.01

first ⅓ avg -0.01 → last ⅓ avg -0.02

Reaction time565ms−48ms

first ⅓ avg 613ms → last ⅓ avg 565ms

Headshot accuracy22.7%+2.0%

first ⅓ avg 20.7% → last ⅓ avg 22.7%

Rolling 5-match average across the last 100 tracked matches, oldest to newest. The delta compares the first third of the window with the last.

Highlights

0.39Best rating — anubis 5–0

13–2Biggest win — overpass

6Longest win streak

W6Current streak

7–9In matches decided by ≤2 rounds

7Overtime games

Map breakdown

infernoBest map · 60% over 10trainWeakest map · 20% over 5

Map	Grade	Played	Record	Win rate	Avg rating
nuke	C	19	7–12	37%	-0.01
cache	C	18	8–10	44%	-0.03
mirage	A	14	8–6	57%	-0.01
dust2	B	12	6–6	50%	-0.03
anubis	A	11	6–5	55%	0.03
inferno	A	10	6–4	60%	0.02
ancient	B	8	4–4	50%	-0.02
train	D	5	1–4	20%	-0.04
overpass	—	2	2–0	100%	0.05
vertigo	—	1	0–1	0%	0.01

Across the last 100 tracked matches.

Lifetime stats

152,522Lifetime kills

1.69K/D · Top 5% of tracked players

6,260Matches

46.4%Match win rate · Top 50% of tracked players

57.3%Headshot % · Top 25% of tracked players

11.6%Shot accuracy

14,038MVPs

2,188Hours (in match)

4,312Bombs planted

1,233Bombs defused

Most-used weapons

AK-4762,317

M4A4 / M4A1-S16,692

AWP13,908

Desert Eagle10,401

P2000 / USP-S6,575

Glock-185,620

Galil AR4,487

MP93,055

SG 5532,347

SSG 082,250

Lifetime map wins

7,625nuke

7,403inferno

4,229vertigo

3,348dust2

1,178train

1,167office

1,054lake

890cbble

Lifetime totals via Steam — visible because this profile's game details are public. Spans CS:GO and CS2.

Faceit stats

Combat

98Matches

46%Win rate

0.93Avg K/D

75.5ADR

47%Headshot %

Clutches & streaks

30%1v1 clutch win

20%1v2 clutch win

6Longest win streak

Recent Faceit resultsWLLLW

Map	Matches	Win rate	Avg K/D	Avg kills
Ancient	23	48%	1.00	15.6
Mirage	20	35%	0.84	14.4
Anubis	16	56%	0.94	12.2
Inferno	14	43%	0.89	13.4
Nuke	11	45%	1.06	14.6
Vertigo	2	0%	0.74	12.0
Dust2	2	100%	1.12	16.0
Train	1	100%	1.77	23.0

Faceit-match stats via the FACEIT Data API — a separate match pool from the sections above.

Skill profile

Aggregate performance across tracked matches — stats via Leetify. Percentile context against other CSDB-tracked players arrives as our own benchmark data accumulates.

22.6%Headshot accuracy

31.4%Accuracy (enemy spotted)

32.0%Spray accuracy

82.5%Counter-strafing

7.5°Preaim

563msReaction time

36.2%T opening success

51.3%CT opening success

0.73Enemies flashed / flash

4.5%Flash assists

12.38HE damage / grenade

8.80Flashes / match

Recommended for you

Chosen by comparing your tracked metrics against the thresholds we flag — the measurement behind each one is shown, so you can disagree with it.

Advanced Mechanics
You are losing most of the first duels you take on T side, which is usually a peeking and spacing problem, not aim.
T opening duels 36.245% — below the 40% mark we flag

Spend your practice time on Train

Map knowledge compounds faster than mechanics — lineups and callouts you learn once keep paying out every time the map comes up.

20% win rate across 5 tracked games — your weakest map with enough games to be worth reading into.

Train callouts & strategy →

Recent matches

Map	Score	Rating	HS%	Date
anubis	13–11	0.03	26%	28 Aug →
cache	13–9	0.01	20%	28 Aug →
mirage	13–5	0.07	23%	28 Aug →
dust2	13–8	-0.09	29%	27 Aug →
mirage	13–8	-0.07	14%	27 Aug →
mirage	13–5	0.07	10%	27 Aug →
dust2	7–13	-0.06	21%	27 Aug →
train	11–13	-0.06	17%	24 Aug →
cache	13–7	-0.05	27%	24 Aug →
mirage	13–7	-0.00	38%	24 Aug →
ancient	6–1	-0.06	19%	24 Aug →
inferno	13–4	0.16	23%	24 Aug →
cache	13–4	-0.05	30%	23 Aug →
nuke	12–12	-0.03	23%	23 Aug →
train	10–13	-0.07	20%	23 Aug →
inferno	11–13	-0.02	23%	23 Aug →
cache	4–13	-0.07	23%	23 Aug →
nuke	10–13	-0.01	29%	14 Aug →
ancient	13–3	0.11	24%	14 Aug →
mirage	12–12	-0.07	22%	13 Aug →
train	8–13	-0.04	34%	13 Aug →
train	13–8	-0.02	28%	11 Aug →
dust2	4–13	0.01	30%	11 Aug →
inferno	3–13	-0.02	30%	11 Aug →
vertigo	9–13	0.01	21%	11 Aug →
nuke	4–13	-0.07	17%	9 Aug →
anubis	13–10	-0.03	18%	9 Aug →
cache	6–13	-0.09	13%	8 Aug →
dust2	8–13	-0.02	17%	8 Aug →
mirage	12–12	-0.02	12%	8 Aug →
inferno	13–8	-0.01	22%	25 Jul →
nuke	13–8	0.03	25%	23 Jul →
anubis	11–13	-0.00	21%	23 Jul →
cache	3–13	-0.05	21%	22 Jul →
anubis	5–0	0.39	21%	22 Jul →
dust2	0–9	-0.08	25%	22 Jul →
anubis	12–12	0.06	13%	22 Jul →
ancient	13–10	-0.09	16%	22 Jul →
inferno	13–5	0.01	31%	22 Jul →
cache	7–13	0.04	19%	22 Jul →
anubis	9–13	-0.05	22%	22 Jul →
mirage	2–0	0.00	0%	22 Jul →
dust2	8–13	0.02	5%	22 Jul →
mirage	11–13	-0.04	22%	16 Jul →
mirage	13–3	0.00	13%	16 Jul →
anubis	13–8	-0.07	12%	16 Jul →
ancient	6–13	-0.03	19%	16 Jul →
nuke	13–11	-0.01	19%	15 Jul →
train	5–13	-0.02	21%	15 Jul →
mirage	11–13	-0.03	21%	15 Jul →
dust2	13–6	-0.01	24%	15 Jul →
cache	13–8	0.01	16%	12 Jul →
ancient	14–16	0.02	28%	17 Jun →
dust2	13–16	-0.06	29%	17 Jun →
nuke	10–13	-0.03	26%	16 Jun →
cache	7–13	-0.03	28%	11 Jun →
anubis	13–7	-0.01	28%	11 Jun →
ancient	9–13	-0.05	23%	11 Jun →
anubis	13–8	0.00	22%	10 Jun →
nuke	5–13	0.05	22%	10 Jun →
inferno	13–5	0.01	23%	10 Jun →
nuke	9–13	-0.00	22%	6 Jun →
inferno	11–13	-0.03	18%	5 Jun →
nuke	13–11	0.00	24%	5 Jun →
nuke	9–13	-0.08	21%	5 Jun →
dust2	13–11	-0.02	13%	5 Jun →
overpass	13–2	0.12	20%	5 Jun →
overpass	13–9	-0.02	23%	5 Jun →
mirage	13–5	0.02	19%	5 Jun →
anubis	12–16	-0.03	21%	4 Jun →
ancient	15–15	-0.05	25%	4 Jun →
nuke	13–9	0.02	34%	4 Jun →
nuke	9–13	-0.04	30%	3 Jun →
nuke	13–7	-0.06	17%	3 Jun →
mirage	13–9	-0.04	18%	3 Jun →
nuke	6–13	-0.04	24%	2 Jun →
inferno	12–12	0.05	14%	25 May →
dust2	13–8	-0.07	14%	25 May →
nuke	13–9	0.00	31%	24 May →
dust2	13–9	0.02	17%	24 May →
mirage	13–16	0.05	22%	16 May →
nuke	13–16	0.04	22%	16 May →
nuke	8–13	-0.00	20%	16 May →
mirage	10–13	-0.05	3%	15 May →
anubis	7–13	0.00	19%	15 May →
nuke	11–13	0.04	14%	15 May →
inferno	13–10	0.09	16%	12 May →
inferno	13–8	-0.04	18%	8 May →
nuke	13–7	0.06	32%	8 May →
dust2	13–11	-0.00	24%	8 May →
ancient	16–14	0.03	15%	4 May →
cache	10–13	0.02	19%	3 May →
cache	11–13	-0.11	6%	30 Apr →
cache	13–8	-0.03	15%	30 Apr →
cache	13–5	0.00	20%	30 Apr →
cache	13–10	-0.03	39%	30 Apr →
cache	0–8	-0.08	9%	30 Apr →
cache	5–13	-0.09	21%	29 Apr →
cache	13–5	0.01	34%	29 Apr →
cache	5–13	0.03	23%	29 Apr →